I. Price Curve Comparison & Cost of Changing Slope

Since October, the competitive landscape of SocialFi has gradually become clearer, with some competitors gradually fading from the market view. Looking back at the development process of Friend.tech, the economic model (especially the pricing curve) has played a very crucial role. Specifically, Friend.tech’s pricing curve has the following characteristics:

1) The positive and negative differences ensure that as the number of users increases, the price continues to rise, and it rises faster and faster, ensuring that early users make money.

2) 16,000 achieves a relatively reasonable community size capacity.

3) As the number of users increases (especially after 100–200), the curve becomes steeper, price fluctuations become higher, and the capacity gradually weakens.

4) The leftmost part of the curve is the most profitable buying range at the moment, but this part is monopolized by bots, forming a revenue form similar to “MEV.”

For a more detailed explanation, you can refer to: https://mirror.xyz/lokiz.eth/w1WKevEM3AAHaS-eDXIiRPU0DtzY6TCiQ_a8eX3tlIA

Regarding competitors, Cipher, PostTech, and NewBitcoinCity have retained Friend.tech’s formula completely, and all protocols are still constructed in the form of quadratic functions, retaining the characteristics of the first derivative > 0, second derivative > 0, and third derivative = 0. This characteristic ensures that Friend.tech’s FOMO/money-making effect continues to exist.

The curve change of New Bitcoin City mainly comes from changes in the valuation base currency and BTC price, while SA and TOMO have made some adjustments to the curve’s shape. SA, in addition to the quadratic term (K²), added a linear term and a constant term, and reduced the coefficient of the linear term. This change theoretically makes the curve overall smoother (rising more slowly) and the initial price higher, but because SA’s constant term value is very small, this change is not easily noticeable. TOMO’s change is simpler, it only reduced the coefficient of the quadratic term by about 73%.

SA and TOMO essentially change the growth rate of the curve. Based on this change, with the same key supply quantity, the prices of SA and TOMO will be lower, with SA’s price level roughly between 15% and 20% of FT’s and TOMO’s price at 37% of FT’s.

In summary, this change is not particularly innovative, and a smoother price curve is a double-edged sword for copycats. On the one hand, FT provides a benchmark value, and it is reasonable for the price of the same player’s key on a copycat platform to be lower than FT itself. A lower price will bring better acceptance and greater user capacity. But on the other hand, a smoother curve means a poorer wealth effect, which is one of the key factors attracting hundreds of thousands of users to FT.

Of course, a steep price curve is not without cost. The other side of the spiral rise is the spiral decline. In the past week, Friend.tech’s TVL has dropped from 27,000 ETH to 21,000 ETH, a decrease of less than 20%, but the resulting price collapse and the (3,3) betrayal go far beyond that.

II. FT’s Gray Rhino: Net Capital Outflow

FT’s Bot and high fees are visible problems for everyone, and the net capital outflow they bring is killing Friend.tech. As shown in the figure below, Friend.tech’s TVL is entirely derived from user deposits, and the part of PnL generated by user transactions and royalties earned by issuers will remain within the protocol if not withdrawn but used for reinvestment. However, the “MEV income” earned by Bot and the fees earned by the protocol will directly become net capital outflow.

It is difficult to quantify the “MEV income” earned by Bot, but the case of AG, the founder of DWF, joining FT in September, is a typical example. The first buy-in price displayed on FT’s front end is 0.4 ETH, which means Bot directly bought 80+ Keys at an average price of 0.135 ETH. These Keys were gradually sold over the next 48 hours at prices ranging from 1.1 ETH to 1.5 ETH. Based on this estimate, Bots earned approximately 100 ETH in AG’s Room, and all these profits came from user losses.

The fee part is relatively quantifiable. According to DUNE data as of October 25th, the cumulative fees attributed to the project were 13,840 ETH. Based on the highest TVL of 27,000 ETH, users have deposited at least 40,000 ETH. Even without considering Bot MEV income, KOL royalty net withdrawals, and net outflows caused by fake accounts and scams, FT has already taken more than 30% of users’ principal in just three months.

When TVL rises, users don’t feel the impact as strongly. But once TVL enters a downtrend or even just a sideways trend, the impact becomes exceptionally strong. Protocol fees, Bot MEV income + KOL royalty net withdrawals + net outflows from fake accounts and scams, are all brought about by [non-trading], and if we estimate the latter three at 5,000 ETH (which is already very conservative), the total cumulative deposit of users is 45,000 ETH.

As mentioned in previous articles, the book value of Keys is roughly three times the true TVL. So, when TVL is 27,000 ETH, the book value of Keys is approximately 81,000 ETH, compared to the total investment of 45,000 ETH, users have an average positive return of 80%. But when TVL drops to 21,000 ETH, the book value of all Keys drops to 63,000 ETH, and users’ average return drops to 40%. The book return on Keys comes with leverage. If TVL continues to decline to 15,000 ETH, the total book value of users will be equal to their total initial capital, and considering transaction costs and bid-ask spreads, users will be in an overall loss state.

Currently, the (3,3) consensus breakdown of FT has a trend that is spreading to TOMO. If the high fees from the protocol and Bot continue, the collapse of FT and other SocialFi platforms is only a matter of time, and with the decline in book returns, the trend of breakdown will accelerate. We had hoped that, Friend.tech would solve the protocol’s fee collection and Bot issues, but it doesn’t seem like any changes have occurred. And recent changes in the scoring rules have objectively led to increased friction in user transactions; and founder 0xRacer has also withdrawn a high amount of fees earned from his Keys.

III. How Can the Curve Be Further Improved?

Further consideration, if we still maintain the premise of P = K²/C+ D (where C and D are constants) for the pricing formula, we need to consider the following factors when setting the pricing formula:

· Curve Growth Rate & Price

A faster growth rate creates more FOMO, mainly achieved by increasing the constant C. Competitors generally reduce the growth rate to make the curve smoother. However, the main purpose of this approach is to maintain a lower price for Keys since the TVL of copycats will be significantly lower than FT, so having a lower price for the same holder makes sense.

· The Number of People the Community Can Accommodate

The curve’s growth rate also determines the upper limit of the community’s capacity. If a higher number of people need to be accommodated, the curve needs to be smoother by:

1) Increasing the constant C

2) Setting a piecewise function, with the later segments being smoother

3) Calculating the corresponding ratio between P and FT-Key’s P for the same X (MEV value at the left end of the curve)

· Solving “MEV problem” Caused by Bots

(1) Increase the positive intercept term D to ensure the initial price is > 0 (Tomo has set D, but its value is low and can be ignored). This approach also has drawbacks: it reduces the multiplier of the wealth effect.

(2) Add a smooth or horizontal curve at the left end

(3) Implement fixed-price IDO (presale system, different from 2 in that one is first-come-first-served and the other is a fair launch)

(4) Allow room owners to pre-purchase

From the perspective of curve shape, there are two categories of improvement approaches. One is to directly change the parameters C and D. This is the most common way to improve currently, and by changing the constant D, it can also solve the MEV problem to some extent.

The second form is to set piecewise functions. This approach can set different parameters in different price range intervals to achieve different purposes. For example, in the first half of the curve, a smoother or even flat curve can be set to resist MEV or facilitate a sort of IDO launch. The IDO mode has a positive impact on solving the Bot MEV and issuance failures (which are more prominent on TOMO).

This also comes at a cost. If a flat curve is adopted on the left end, the wealth effect of the opening will be greatly weakened, and the supply quantity on the left end needs to be considered further, as an excessive supply may consume potential buy orders or wealth effects.

IV. Beyond KOLs, What Else Can Keys Carry?

An objective fact is that the “services” or “information” provided by most Room Owners are not sufficient to support the value of Keys, or in other words, the price of Keys is generally overestimated. The reason for this problem is that, Friend.tech’s speculative demand and point-scoring demand have blurred the lines of true utility demand, and FT and its copycats have made price curve choices based on business purposes.

Most people simply use Keys as social tokens, but in fact, Keys can represent any asset. Friend.tech has given us an idea: to introduce “Fi” into “Social” by connecting asset issuance and trading to complete the final closed loop of SocialFi. For FT and most copycats, Keys represent the personal brand or reputation of KOLs, but this does not mean SocialFi is limited to this. Even if it is still based on FT, any asset can be loaded into Keys, such as equity or tokens of Web3 projects (some have already done so), in which case Keys represent the tokens or shares; or using FT to conduct IDOs, Keys represent investment shares or future redemption rights (perhaps some projects will do this soon).

Currently, it seems that the functions of FT and copycats are too simple and do not meet some derivative demands well. Another approach is to introduce [asset issuance] into existing Web3 social/content products (such as DeBox, CrossSpace, etc.). For example, DeBox is positioned as the most native DAO governance platform and has already built a social platform with chat, dynamics, and community functions based on DID, as well as components for voting, proposals, token authorization detection, and transactions. With a large number of users, strong social connections, information, management tools, and transaction tools, DeBox, which currently has 1.5 million registered users and over 100 million daily messages, has a high level of scalability on the functional level and is naturally suitable for introducing an effective asset issuance solution and an economic model and price curve adapted to the business type.

Here, assets include but are not limited to specific content, decentralized groups, or even MEMEs with no substantial meaning but a common group will. A series of social tools and infrastructure services will provide services to these assets, and the value of Keys will truly complete the loop.

Finally, the biggest difference between Fi and Ponzi is whether assets exist and have value, and we must never ignore this point.